.ZIP
2DScanImages.zip (11.89 GB)
DATASET
Method_Image_Replicate_Codebook.csv (1.34 kB)
DATASET
Variable_Codebook.csv (9.82 kB)
TEXT
2D_Digital_Readme.txt (3.65 kB)
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Longitudinal Shoe Study: 2D Scan Images
Version 2 2020-02-03, 22:20
Version 1 2019-11-26, 15:09
dataset
posted on 2020-02-03, 22:20 authored by Susan VanderplasSusan Vanderplas, Alicia Carriquiry, James Kruse, Guillermo Basulto-Elias, Stacy RenfroImages of shoe prints from 160 pairs of shoes (“Nike Winflo 4” or “Adidas Seeley”; 4 sizes each) made using a 2D digital scanner (EverOS EverSpry) with associated measurements and data about shoe wear, surfaces, and wearers.
Each pair of shoes was worn for at least 10,000 steps per week over a 6-month period, with multiple measurements of the shoe soles taken initially and during three check-in periods spaced at approximately 5 week intervals.
The images are accompanied by 3 CSV files describing the shoes, visit (information collected from surveys along with the shoes), and individual images. The codebooks contain descriptions of the variables in each of the CSV files as well as a more extensive description of the file naming scheme outlined in the README.
These files can be used to examine wear pattern development, to look for the presence of identifying characteristics among shoes with similar features, and to develop algorithms for matching shoes based on individualizing characteristics.
Each pair of shoes was worn for at least 10,000 steps per week over a 6-month period, with multiple measurements of the shoe soles taken initially and during three check-in periods spaced at approximately 5 week intervals.
The images are accompanied by 3 CSV files describing the shoes, visit (information collected from surveys along with the shoes), and individual images. The codebooks contain descriptions of the variables in each of the CSV files as well as a more extensive description of the file naming scheme outlined in the README.
These files can be used to examine wear pattern development, to look for the presence of identifying characteristics among shoes with similar features, and to develop algorithms for matching shoes based on individualizing characteristics.
